Cover Image

NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Zhonghao, Sun, Danyu, Zhou, Sheng, Wang, Haobo, Fan, Jiapei, Huang, Longtao, Bu, Jiajun
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Social and Information Networks
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Correlation-Aware Graph Convolutional Networks for Multi-Label Node Classification
by: Bei, Yuanchen, et al.
Published: (2024)

OpenGT: A Comprehensive Benchmark For Graph Transformers
by: Tang, Jiachen, et al.
Published: (2025)

Heterophilous Distribution Propagation for Graph Neural Networks
by: Zheng, Zhuonan, et al.
Published: (2024)

Revisiting the Message Passing in Heterophilous Graph Neural Networks
by: Zheng, Zhuonan, et al.
Published: (2024)

Local Graph Clustering with Noisy Labels
by: de Luca, Artur Back, et al.
Published: (2023)

Macro Graph Neural Networks for Online Billion-Scale Recommender Systems
by: Chen, Hao, et al.
Published: (2024)

An Algorithm for Computing the Capacity of Symmetrized KL Information for Discrete Channels
by: Chen, Haobo, et al.
Published: (2024)

Better Late Than Never: Formulating and Benchmarking Recommendation Editing
by: Lai, Chengyu, et al.
Published: (2024)

Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation
by: Wang, Yuxiang, et al.
Published: (2025)

Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection
by: Bei, Yuanchen, et al.
Published: (2024)

A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges
by: Ju, Wei, et al.
Published: (2024)

Learning to Retrieve with Weakened Labels: Robust Training under Label Noise
by: Sharma, Arnab
Published: (2025)

The Fisher-Rao Loss for Learning under Label Noise
by: Miyamoto, Henrique K., et al.
Published: (2022)

MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction
by: Qian, Hao, et al.
Published: (2024)

Towards Differential Privacy in Sequential Recommendation: A Noisy Graph Neural Network Approach
by: Hu, Wentao, et al.
Published: (2023)

Spectral-Based Graph Neural Networks for Complementary Item Recommendation
by: Luo, Haitong, et al.
Published: (2024)

HGAMN: Heterogeneous Graph Attention Matching Network for Multilingual POI Retrieval at Baidu Maps
by: Huang, Jizhou, et al.
Published: (2024)

Graph and Sequential Neural Networks in Session-based Recommendation: A Survey
by: Li, Zihao, et al.
Published: (2024)

The Expressive Power of Graph Neural Networks: A Survey
by: Zhang, Bingxu, et al.
Published: (2023)

Incremental Label Distribution Learning with Scalable Graph Convolutional Networks
by: Jia, Ziqi, et al.
Published: (2024)

The Effect of Label Noise on the Information Content of Neural Representations
by: Umar, Ali Hussaini, et al.
Published: (2025)

Graph-Theoretic Characterization of Noise Capacity of Conditional Disclosure of Secrets
by: Li, Zhou, et al.
Published: (2025)

Privacy-Resolution Tradeoff for Adaptive Noisy Twenty Questions Estimation
by: Sun, Chunsong, et al.
Published: (2026)

Cold-Start Recommendation towards the Era of Large Language Models (LLMs): A Comprehensive Survey and Roadmap
by: Zhang, Weizhi, et al.
Published: (2025)

Neighborhood Overlap-Aware High-Order Graph Neural Network for Dynamic Graph Learning
by: Wang, Ling
Published: (2025)

Non-GRS type Euclidean and Hermitian LCD codes and Their Applications for EAQECCs
by: Liang, Zhonghao, et al.
Published: (2026)

Noisy Sorting Capacity
by: Wang, Ziao, et al.
Published: (2022)

Chi-Square Wavelet Graph Neural Networks for Heterogeneous Graph Anomaly Detection
by: Li, Xiping, et al.
Published: (2025)

Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
by: Laakom, Firas, et al.
Published: (2025)

Social Networks: Enumerating Maximal Community Patterns in $c$-Closed Graphs
by: Bourla, Gabriela, et al.
Published: (2025)

Debiased Recommendation with Noisy Feedback
by: Li, Haoxuan, et al.
Published: (2024)

Adaptive Beam Alignment using Noisy Twenty Questions Estimation with Trained Questioner
by: Sun, Chunsong, et al.
Published: (2026)

Cluster-Enhanced Federated Graph Neural Network for Recommendation
by: Wang, Haiyan, et al.
Published: (2024)

Two-Stage Stance Labeling: User-Hashtag Heuristics with Graph Neural Networks
by: Melton, Joshua, et al.
Published: (2024)

Graph Neural Networks for Source Detection: A Review and Benchmark Study
by: Sterchi, Martin, et al.
Published: (2025)

Understanding and Mitigating the Bias in Sample Selection for Learning with Noisy Labels
by: Wei, Qi, et al.
Published: (2024)

Channel Polarization under Channel Noise with Memory
by: Qi, Tianfu, et al.
Published: (2024)

Diffusion-augmented Graph Contrastive Learning for Collaborative Filter
by: Huang, Fan, et al.
Published: (2025)

Disambiguated Node Classification with Graph Neural Networks
by: Zhao, Tianxiang, et al.
Published: (2024)

Neural Causal Graph Collaborative Filtering
by: Wang, Xiangmeng, et al.
Published: (2023)